QI 106 Lesson 4: A Deeper Dive into Run Charts
When you analyze a run chart, you’re looking for non-random patterns in the data — that is, evidence that performance has actually changed as a result of your PDSA cycles. But how can you tell if the variation you’re seeing is random or non-random? In this lesson, you’ll practice using four rules to help you “read” a run chart and determine whether your changes have led to improvement.
Estimated Time of Completion: 30 minutes
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Learning Objectives
After completing this lesson, you will be able to:
1. Identify non-random patterns in data.
2. Analyze data using a run chart.
3. Determine whether run charts show that your changes have led to improvement.
Contributors
Author(s):
Kevin Little, Ph.D, Principal, Informing Ecological Design, LLC View Profile
Editor(s):
Kathleen Vega, BA, Freelance Writer, Kathleen B. Vega, Inc View Profile
Reviewer(s):
Matthew Eggebrecht, Senior Consultant, University of Minnesota View Profile
Lloyd Provost, MS, Statistician, Associates in Process Improvement View Profile
Richard Scoville, PhD, Improvement Advisor/Consultant, Institute for Healthcare Improvement View Profile
Requirements
You must be a registered IHI.org user to take this lesson.
You must achieve a minimum score of 75% to successfully complete this lesson.